Project Summary Alzheimer?s disease and related dementia (referred to collectively here as ?dementia?) is estimated to be one of the most costly health conditions in America, with most of the costs coming from long-term services and supports (LTSS) ? help with everyday activities, such as bathing, dressing, grooming, using the toilet, eating, and moving around ? much of which is provided by family. Almost 4 million adults 70 and over receive care from family and friends for cognitive impairment or dementia, and the need for this care will only increase as the nation grows grayer. Quantifying the need for and availability of family care for dementia, as well as quantifying the burden of care on individual caregivers, will help decision-makers adequately prepare for future shortages in the number of dementia caregivers and ensure the well-being of such caregivers. This work will use a variety of data sources and methods to examine the interplay between two trends that appear to be on a collision course: declining family size (lower supply) and increasing numbers of dementia cases (higher demand). Our key innovation is to link an existing demographic microsimulation model (MSM) with data on dementia incidence, thereby providing the first study to examine the future availability of family care for older adults with dementia. While there is some work modeling the demand side of care needs for dementia or other chronic disease incidence, the few studies of the supply side of family care are limited: they do not examine caregiving for dementia in particular, and most also incorporate only a limited definition of family care. We propose to build on a long-standing microsimulation model of expected kinship networks to develop a model of the supply of family care and to use data from the Health and Retirement Study (HRS) and the Aging, Demographics, and Memory Study (ADAMS), a subsample of HRS respondents ages 70 and over, in combination with published data on dementia incidence to develop a demand model of dementia incidence. We will link the two models using data from the HRS on the predictors of dementia care. Data from the HRS will also be used to identify groups at high risk of needing or providing care and on anticipated hours of care from different family members (e.g. spouses, biological kin, step-kin, etc.). Finally, the output of the linked models will be tested under different assumptions about how care patterns and demographic trends will change over time. This combination of information is critical for informing families and policymakers about anticipated shortages in dementia family care, as well as increases in the burden of care on individual family members in the U.S., which is expected to reach new heights as the baby boomers age.